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| A Robust Blind Sparsity Target Parameter Estimation Algorithm for Compressive Sensing Radar |
| Wang Chao-yu① Mei Mei① Zhu Xiao-hua① He Ya-peng② Li Hong-tao① |
①(School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China)
②(Institute of Microwave Remote Sensing and Data Transmission, China Academy of Space Technology, Xi’an 710000, China) |
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Abstract In order to enhance the performance of estimating range-Doppler parameters in presence of mismatch error between sensing matrix and target information vector for Compressive Sensing Radar (CSR), a robust blind sparsity target parameter estimation algorithm is proposed. First, a two-dimensional sparse sensing model for range-Doppler estimation is established when there exists CSR system model mismatch error, and a waveform optimization object function is derived based on minimization Coherence of Sensing Matrix (CSM). Then, a novel blind sparsity CSR algorithm is employed to correct system sensing matrix and estimate the range-Doppler parameters by optimizing iteratively transmit waveform, system mismatch error and target information vector. Compared with traditional CSR algorithm, the proposed method reduces the range-Doppler estimation error, and enhances the accuracy and robustness of CSR target information estimation. The validity of the proposed method is demonstrated with numerical simulation.
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Received: 10 July 2013
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Corresponding Authors:
Wang Chao-yu
E-mail: wangchaoyv@gmail.com
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2014, Vol. 36 
